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用于眼眶诊断的伊莎贝尔鉴别诊断生成器。

The Isabel Differential Diagnosis Generator for Orbital Diagnosis.

作者信息

Ing Edsel B, Balas Michael, Nassrallah Georges, DeAngelis Dan, Nijhawan Navdeep

机构信息

Department of Ophthalmology and Vision Science, University of Toronto Temerty Faculty of Medicine, Toronto, Canada.

Department of Ophthalmolgoy and Vision Science, University of Alberta, Edmonton, Canada.

出版信息

Ophthalmic Plast Reconstr Surg. 2023;39(5):461-464. doi: 10.1097/IOP.0000000000002364. Epub 2023 Mar 16.

DOI:10.1097/IOP.0000000000002364
PMID:36928323
Abstract

PURPOSE

The Isabel differential diagnosis generator is one of the most widely known electronic diagnosis decision support tools. The authors prospectively evaluated the utility of Isabel for orbital disease differential diagnosis.

METHODS

The terms "proptosis," "lid retraction," "orbit inflammation," "orbit tumour," "orbit tumor, infiltrative" and "orbital tumor, well-circumscribed" were separately input into Isabel and the results were tabulated. Then the clinical details (patient age, gender, signs, symptoms, and imaging findings) of 25 orbital cases from a textbook of orbital surgery were entered into Isabel. The top 10 differential diagnoses generated by Isabel were compared with the correct diagnosis.

RESULTS

Isabel identified hyperthyroidism and Graves ophthalmopathy as the leading causes of lid retraction, but many common causes of proptosis and orbital tumors were not correctly elucidated. Of the textbook cases, Isabel correctly identified 4/25 (16%) of orbital cases as one of its top 10 differential diagnoses, and the median rank of the correct diagnosis was 6/10. Thirty-two percent of the output diagnoses were unlikely to cause orbital disease.

CONCLUSION

Isabel is currently of limited value in the mainstream orbital differential diagnosis. The incorporation of anatomic localizations and imaging findings may help increase the accuracy of orbital diagnosis.

摘要

目的

伊莎贝尔鉴别诊断生成器是最广为人知的电子诊断决策支持工具之一。作者前瞻性评估了伊莎贝尔在眼眶疾病鉴别诊断中的效用。

方法

将“眼球突出”“眼睑退缩”“眼眶炎症”“眼眶肿瘤”“浸润性眼眶肿瘤”和“边界清晰的眼眶肿瘤”等术语分别输入伊莎贝尔,并将结果制成表格。然后将一本眼眶外科学教科书中25例眼眶病例的临床细节(患者年龄、性别、体征、症状和影像学表现)输入伊莎贝尔。将伊莎贝尔生成的前10个鉴别诊断与正确诊断进行比较。

结果

伊莎贝尔将甲状腺功能亢进和格雷夫斯眼病确定为眼睑退缩的主要原因,但许多眼球突出和眼眶肿瘤的常见病因未得到正确阐明。在教科书中的病例中,伊莎贝尔正确地将25例眼眶病例中的4例(16%)确定为其前10个鉴别诊断之一,正确诊断的中位排名为6/10。32%的输出诊断不太可能导致眼眶疾病。

结论

目前伊莎贝尔在主流眼眶鉴别诊断中的价值有限。纳入解剖定位和影像学表现可能有助于提高眼眶诊断的准确性。

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引用本文的文献

1
Large Language Models in the Diagnosis of Hand and Peripheral Nerve Injuries: An Evaluation of ChatGPT and the Isabel Differential Diagnosis Generator.大语言模型在手部和周围神经损伤诊断中的应用:ChatGPT与伊莎贝尔鉴别诊断生成器的评估
J Hand Surg Glob Online. 2024 Sep 3;6(6):847-854. doi: 10.1016/j.jhsg.2024.07.011. eCollection 2024 Nov.